As abstract as love can be, two researchers claim that a method called Facebook mapping on couple's mutual friends can predict if couple - whether in a relationship, engaged or married - will likely end up falling apart and separating.

In their paper titled Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook, researchers claimed that couple who shared less of non-mutual friends have 50 per cent chance of breaking-up in the next two months.

The paper was presented by researchers Jon Kleinberg, a computer scientist at Cornell University, and Lars Backstrom, a senior Engineer at Facebook.

To come up with the report, they mapped out Facebook using 1.3 million Facebook users and look into their relationship status. The subjects, who listed being in a relationship, engaged or married, aged from 20 years old and above and had 50 to 2,000 friends. These subjects were tracked every two months in two years time using a measurement called dispersion.

Dispersion is "the extent to which two people's mutual friends are not themselves well-connected," as defined from the report.

According to the researchers, they "organise their analysis around a basic question: given all the connections among a person's friends, can you recognise his or her romantic partner from the network structure alone?"

"Using data from a large sample of Facebook users, we find that this task can be accomplished a high accuracy," the researchers wrote.

"We find that relationships on which recursive dispersion fails to correctly identify the partner are significantly more likely to transition to 'single' status over a 60-day period. This effect holds across all relationship ages and is particularly pronounced for relationships up to 12 months in age; here the transition probability is roughly 50 percent greater when recursive dispersion fails to recognize the partner," as concluded by the report.

Using their entire dispersion algorithm, Kleinberg and Backstrom is targeting to release their findings by February of 2014.

As for Facebook, the research is instrumental for their automated process of tracking its users' relationships in order to choose more relevant content and ads.